Fig. 1 illustrates the hypothetical model, which includes components chosen based on insights from the literature review. Social exchange theory serves as a practical framework for analyzing residents’ perspectives and attitudes toward tourism development, as supported by multiple studies (Diedrich and García-Buades, 2009; Vargas-Sánchez et al., 2009). This theory in tourism posits that residents support tourism development when they perceive the benefits to outweigh the costs (Ap, 1992; Jurowski et al., 1997; Gursoy and Rutherford, 2004; Çelik and Rasoolimanesh, 2021). A positive assessment of social and cultural impacts is directly associated with increased support for tourism development (Brunt and Courtney, 1999; Besculides et al., 2002). In this model, the positive sociocultural impact of tourism is seen as a benefit, while the negative sociocultural impact is regarded as a cost. Because the positive socio-cultural impacts surpassed the negative ones, residents were encouraged toward tourism developments. In the following sections, various elements of exchange that shape perceptions of tourism and influence residents’ responses to tourism are explored in detail.

Climate change now plays a major role in shaping global tourism. The tourism industry relies on natural resources, stable weather conditions, and a healthy ecosystem. At the same time, it contributes to climate change through activities like transportation and hotel operations. Rising temperatures, changing weather patterns, and extreme events, such as hurricanes and wildfires, disrupt travel destinations. (Scott et al., 2012). Rising temperatures are making some locations attractive or even uninhabitable. Melting glaciers threaten mountain resorts and winter sports areas that depend on snow. Rising sea levels are eroding beaches and flooding coastal tourist spots. Coral reefs, which attract divers and marine life enthusiasts, are dying due to ocean warming. These changes are creating serious challenges for the tourism industry in iconic destinations (Gössling et al., 2012). Weather changes are upsetting regular tourism seasons. This affects places that rely on specific weather conditions to attract visitors (Gössling et al., 2012). Increased frequency of hurricanes, floods, and wildfires poses risks to tourist safety and infrastructure (UNWTO, 2008). Climate change has been observed to have particularly severe impacts in the Hindu Kush Himalayan region, including Nepal, due to its high altitudinal variation and fragile geographical structure (Eugenio-Martin and Campos-Soria, 2010; ; K.C., 2017; Richardson, 2021). Climate change can heighten the risk of vector-borne disease (VBD) epidemics in Nepal’s mountain regions, assuming non-climatic factors remain unchanged (Dhimal et al., 2015). Climate change is increasingly linked to potential changes in the incidence of waterborne and diarrheal diseases (Levy et al., 2018). Climate change significantly influences tourist behavior and the tourism industry, making it essential to understand tourists’ knowledge, attitudes, and practices for further development of the tourism sector (Guo et al., 2025). Attitudes toward tourism development in the context of climate change are influenced by the perspectives of tourists, residents, stakeholders, and policymakers. Balancing economic growth with environmental sustainability remains a significant challenge for tourism development (Becken and Hay, 2012). The positive relationship among social, economic, and environmental factors influences the quality of life and support for tourism development (Halim et al., 2022). Shifting climate patterns were driving cultural transformations, impacting livelihood strategies, practices, and the traditional ethno-climatic rituals associated with the four seasons ( Becken et al., 2013). The tourism stakeholders were aware of the general impact of climate change, but it did not have a significant impact on tourism; they envisaged challenges to future business growth (Saarinen et al., 2012). Following these lines of logic, the relationship between climate change and attitudes toward tourism development is proposed as follows.

Nepal’s tourism industry, heavily reliant on trekking, mountaineering, and cultural heritage, faces significant threats from climate change. Melting glaciers, erratic weather patterns, and increased risks of avalanches and landslides affect popular destinations, such as Nepal (Nepal, 2013). Abrupt changes in precipitation trends resulted in more frequent floods, droughts, landslides, and soil erosion (Spijkers, 2011). Climate change can impact tourism by altering the appeal of destinations, disrupting infrastructure, damaging natural resources, affecting tourist satisfaction and safety, and influencing the sustainability of facilities and destinations (Becken and Hay, 2007). Climate change has led to direct losses in Asia by damaging infrastructure, disrupting services, and impacting supply chains. Beyond escalating infrastructure risks, it is also projected to generate opportunities for climate-resilient infrastructure and green jobs (Shaw et al., 2022). Climate change exerts substantial pressure on the tourism sector by disrupting environmental and socio-economic conditions that shape tourist behavior and destination appeal. Rising temperatures, shifting precipitation patterns, and more frequent extreme weather events impact tourism demand and the sustainability of the infrastructure, natural attractions, and destination accessibility (Tanrisever et al., 2024). Climate change disrupts Himalayan tourism by transforming landscapes and ecosystems, impacting adventure tourism and posing socio-economic challenges for local communities, including income loss and threats to cultural heritage preservation (Saxena et al., 2024). Climate change moderately impacts tourism by affecting the operational and profitability aspects of destinations, shifting tourist demand, and influencing broader socio-economic conditions, challenging business operations, and community adaptation and resilience (Lixin, 2024). Climate change is causing shifts in flowering periods in complex and diverse patterns, even in small local areas (Prevéy, 2020). Based on the interplay between the climate change impacts on tourism and residents’ attitudes toward further tourism developments, the hypotheses are proposed as follows;

The sociocultural impacts of tourism encompass both positive and negative effects on host communities, influencing cultural preservation, community dynamics, and social structure. Understanding these impacts is crucial for the sustainable development of tourism. The sustainability and tourism development rely on residents’ perceptions of its sociocultural impact on their communities (Látková and Vogt, 2012; Lee, 2013; Vidal Rua, 2020). Many studies have explored how residents perceive the sociocultural effect of tourism development (Easterling, 2005; Deery et al., 2012) and numerous studies highlighted a wide range of differing perspectives among various resident groups concerning the sociocultural effects of tourism development (Haralambopoulos and Pizam, 1996; Easterling, 2005). Several researchers have identified causal links between the perceived advantage of tourism and the level of support for it (Gursoy et al., 2019). The sociocultural impact of tourism involves changes to traditional values, lifestyles, and interpersonal relationships within host communities. Positive sociocultural impacts encompass enhancements in social services (Andereck et al., 2005; Deery et al., 2012), transportation and recreation facilities (Sharma et al., 2008; Marzuki, 2011), improving the understanding and image of different communities (Andereck et al., 2005), and demand for historical and cultural activities (Marzuki, 2011; Liu et al., 2012).

Negative socio-cultural impact of tourism development is overcrowding and traffic congestion (Jurowski and Gursoy, 2004; Andereck et al., 2005), increased crime, robberies, alcoholism, prostitution, use of drugs (Andereck et al., 2005; Marzuki, 2011; Deery et al., 2012). Climate change significantly impacts tourism by causing revenue decline, employment challenges, and sea level rises, potentially forcing communities to relocate, which leads to loss of cultural heritage and community cohesion (Saxena et al., 2024). Residents’ support for tourism development is influenced by their attitudes towards sustainable tourism and an understanding that sociocultural impacts are crucial, as positive attitudes can foster sustainable tourism and ensure local communities’ benefits. Perceived social costs reduce support, while economic benefits, environmental sustainability, community participation, long-term planning, and visitor satisfaction enhance it (Dogan and Tekeli, 2024). The interaction between the socio-cultural impact of tourism and attitudes toward further tourism development indicated the following hypotheses.

This study examines the factors influencing attitudes toward tourism development in three vulnerable districts of Western Nepal (Mustang, Lamjung, and Kaski), selected based on their vulnerability indices (high in Lamjung and Mustang, moderate in Kaski). Located within the bio-diverse Annapurna Conservation Area (ACA), these districts are renowned for their unique ecological landscapes, wildlife, and trekking tourism. Mustang is characterized by its rocky terrain and cultural heritage sites, Lamjung by homestays and historical landmarks, and Kaski by its scenic mountainous views. Covering an area of 7,282 km². The study area map is shown in Fig. 2.

The three districts studied have a total population of 674,418. From the Kaski district, one rural municipality and one metropolitan area were selected; from Lamjung, one rural municipality and one municipality were chosen; and from Mustang, four rural municipalities were selected randomly. A total of 490 respondents were selected from two urban areas and six rural municipalities in proportion to their population sizes. The survey primarily relies on a Likert scale, so the Kish (1965) formula was employed to determine the sample size.

Where, Z_∝/2 =1.96 at 0.05 level of significance, C = Coefficient of variation of Likert items ( 0.8), K = Number of constructs (10), ρ = Correlation coefficient (0.4), D = Error (0.05). We obtained a sample size of approximately 490, accounting for a 10% non-response rate. Primary data were collected from August to December 2022 through structured questionnaire interviews and informal discussions with key informants, including local leaders, teachers, and elders, with a focus on the impact of climate change on tourism and its development. A structured, pre-tested questionnaire, validated through expert discussions and literature reviews, was utilized. Reliability was confirmed by Cronbach’s alpha (0.913), while validity was ensured using the Pearson test. A variance inflation factor of less than 5 indicated that there were no multicollinearity issues.

This study employs a quantitative approach and utilizes a cross-sectional research design, using the SmartPLS software package. Partial least squares structural equation modeling (PLS-SEM) is an emerging data analysis tool for business and social science research, particularly when the data are non-normal and the sample size is small. PLS-SEM involves two stages of analysis: the measurement model and the structural model.

The survey collected demographic data, including gender, age, marital status, religion, income, occupation, region, and education level (Table 1).

This study established a research model based on previous studies that identified the factors affecting attitudes toward tourism development and determined the mediation effect. The measurement model was evaluated following the guidelines of Hair Jr. et al. (2022) to ensure construct reliability and validity. Initially, 38 indicators were included; however, any indicator with a loading factor of less than 0.6 was removed from the iterative analysis, retaining theoretically significant indicators while maintaining the average variance extracted and composite reliability. This process resulted in 29 indicators in the final model. The variables included in the model were the impact of climate change, the impact of climate change on tourism, sociocultural factors (both positive and negative), and attitudes toward tourism development, along with their indicators, as shown in Table 2.

The mean and standard deviation of the indicators included in the model are presented in Table 3, which also includes loading values, Cronbach’s alpha, composite reliability, and average variance extracted for each indicator and its corresponding factors. It indicated that the model is reliable, valid, and established because the value of Cronbach’s alpha and composite reliability is more than 0.7, and the average variance extracted was more than 0.5 (Table 3).

Table 4 demonstrates that the square root of the average variance extracted for each construct exceeds its correlation with other latent variables, confirming the construct was a valid measure of distinct concepts. The Heterotrait-Monotrait (HTMT) ratio was below 0.85, ensuring discriminant validity. Additionally, each indicator’s outer loading on its associated construct is higher than its cross-loading on another construct, meeting cross-loading criteria. Thus, all requirements for discriminant validity, cross-loading, Fornell-Larcker, and HTMT are satisfied.

Bold-faced and italicized diagonal values are the square root of AVE. Lower off-diagonal values are inter-construct correlations. Upper off-diagonal elements are HTMT values.

After validating the measurement model, the structural model is evaluated. Fig. 3 illustrates the structural model, including the construct with its slope, p-value, and indicators, along with loading values and significance levels. To test the significance of the model’s path coefficient, the bootstrapping was performed with 5,000 resamples. This method generates an empirical distribution of estimates by randomly resampling the dataset with replacement, allowing for the calculation of stable standard errors, confidence intervals, and p-values. It shows that all the loading values are greater than 0.7, except for B04.7 (Tourism reduced migration), and the PLS-SEM analysis of residents’ perceptions towards tourism development. The model is valid because all the indicators are significant at the 0.05 level of significance, and all the constructs meet the reliability (CR > 0.8 indicates internal consistency) and validity (AVE > 0.5 confirms convergent validity) thresholds. The model’s predictive power was assed using Stone-Geisser’s Q² ( > 0.01 suggests predictive relevance).

Table 5 presents the hypotheses, relationships, path coefficients, and T and P values. Furthermore, the model validation metric, the coefficient of determination (R²), is calculated to assess the model’s performance. The results support hypothesis H₁, indicating that while the effect size (β = 0.051) is small, the relationship is statistically significant (p < . 001). It predicts that the impact of climate change has a positive effect on the sociocultural factor, as a result of increasing temperatures, the length of the tourism season in Nepal has increased. Hypothesis H₂ is supported and shows significant empirical evidence that the impact of climate change has positive and statistically significant influences on sociocultural factors (negative). As a result of floods and landslides, vulnerable individuals are significantly influenced, with a moderate but substantial effect (β = 0.204). The impact of climate change on tourism development is negligible, with a minimal effect (β = 0.075). Hence, the hypothesis is rejected. It is because the touristic infrastructure is mostly city-centered and less affected by climate change. The impact of climate change on the tourism sector has positively influenced society and its attitude towards tourism, with a moderate level of impact. Hypotheses H₄ and H₆ are significant. The impact is insignificant in terms of the negative sociocultural factors. Hence, the hypothesis H₅ is rejected, but the strength is high, indicating that it does not support tourism development. This is because they perceived tourism as a curse rather than an opportunity. As a result, H₈ is rejected, and residents are not motivated to further tourism development. The sociocultural impact of tourism has a positive influence on the development of the tourism sector, with a moderate strength (β = 0.198).

To investigate how the socio-cultural impact of tourism mediates various factors, we employed the methods outlined by Preacher and Hayes (2008). We obtained the t-value and p-value for indirect effects through bootstrapping with 5,000 resamples, as described by Hair Jr et al. (2022). The results in Table 6 indicate a significant, indirect, and positive socio-cultural impact on tourism development. This suggests that the positive socio-cultural impact of tourism contributes to the advancement of tourism development. Median analysis revealed that the sociocultural factor serves as a strong mediating factor influencing the tourism sector. Society perceived tourism as an opportunity; they warmly welcomed tourists and were motivated to develop the tourism industry during the initial phase of tourism development. As the number of tourists increased and surpassed the destination’s carrying capacity, the benefits of tourism outweighed the costs, and residents are not interested in tourism development.

This research examines the impact of climate change on tourism development, with a focus on the mediating role of socio-cultural factors. The study has three primary objectives. First, it aims to analyze the effects of climate change and its specific implications for tourism development. Second, it seeks to explore the socio-cultural impacts on tourism development. Third, it examines how socio-cultural factors mediate the relationship between climate change and tourism development.

The results of the structural model path coefficients provide valuable insights into the relationships between climate change impacts, socio-cultural factors, and attitudes toward tourism development (ATD). These findings align with, and in some cases contradict, existing literature, offering a nuanced understanding of the dynamics at play.

This hypothesis was tested using the PLS-SEM technique, which revealed that climate change impacts socio-cultural factors significantly, both positively and negatively. This aligns with studies (Becken and Hay, 2007; Gössling et al., 2012), which highlight how climate change can reshape cultural practices, community resilience, and tourism experiences. Interestingly, the impact of climate change on tourism does not significantly affect the negative sociocultural impacts. This contradicts the finding of Alamineh et al. (2023), who argue that tourism-dependent communities often experience heightened sociocultural stress due to climate-induced changes. Positive sociocultural impacts play a crucial role in shaping attitudes toward tourism development. However, negative sociocultural impacts and certain direct effects of climate change do not significantly influence attitudes toward tourism development.

This study validates social exchange theory (SET), demonstrating that residents support tourism when the perceived benefits (SCOP) outweigh the costs. It highlights the mediation role of positive socio-cultural impacts in shaping attitudes towards tourism development, adding new depth to research.

Tourism development strategies in climate-vulnerable regions, such as Nepal, must integrate sociocultural well-being alongside economic gains. Since direct climate change effects do not deter tourism support, adaptation strategies should focus on indirect pathways (e.g., preserving cultural assets). The findings apply to other mountainous and ecologically sensitive regions facing similar climate threats. Balancing environmental sustainability, cultural integrity, and economic viability is key to long-term tourism resilience.

The study emphasizes that while climate change poses challenges, positive sociocultural impacts play a crucial mediating role in sustaining tourism development. Policymakers should adopt inclusive, adaptive, and sustainable tourism models to ensure community support and environmental preservation in Nepal’s Annapurna Conservation Area and similar regions.

While this research provides valuable insights into the relationship between climate change, sociocultural factors, and tourism development in ACA, some limitations must be acknowledged. The study’s reliance on a quantitative survey may not fully capture the region’s sociocultural diversity or reflect the broader Nepalese context, limiting generalizability. The cross-sectional design prevents causal inference about how climate change impacts tourism over time. In the absence of qualitative data leaves the sociocultural mediation mechanism underexplored. This study does not account for critical factors like policy intervention in tourism benefits.

This study focuses on the general climate change impact (IMP_CC) and tourism-specific climate effect (IMP_CCT). Future research could examine the specific climate-related threats (such as glacier retreat, biodiversity loss, and extreme weather events) and their direct influence on tourism attitudes. Climate change effects evolve; longitudinal research could track shifts in residents’ perceptions and adaptation strategies. The mediating role of sociocultural factors was examined; future studies could assess quality of life, economic benefit, and environmental degradation as additional mediators. Further research investigates the moderating effects of various factors (e.g., community resilience, government tax policy) on the relationship between climate change and tourism attitudes. Qualitative research and a mixed methods approach may explore why the negative sociocultural factors and others were not supported, uncovering nuanced local perspectives.